C. Eric
Impact in
- Computational Mathematics top 0.5%
- Tensor decomposition and applications
- Statistics and Probability top 5%
- Statistical Methods and Inference
Papers in
-
- Sparse and Compressive Sensing Techniques 14
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- Bayesian Methods and Mixture Models 6
- Advanced Clustering Algorithms Research 4
- Co-authors
- Kenneth Lange (11 shared papers)Tamara G. Kolda (1 shared paper)Richard G. Baraniuk (4 shared papers)Hua Zhou (8 shared papers)Genevera I. Allen (3 shared papers)Gary K. Chen (2 shared papers)John Michael O. Rañola (1 shared paper)David W. Scott (1 shared paper)
- Journals
- Journal of Computational and Graphical Statistics (5 papers)Technometrics (2 papers)The American Statistician (2 papers)Scientific Reports (1 paper)Computational Statistics & Data Analysis (1 paper)
- Partner nations
- United StatesPolandFrance
In The Last Decade
C. Eric
38 papers receiving 720 citations
Peers
Comparison fields: 5 of 110
- Computational Mathematics 170
- Statistics and Probability 125
- Artificial Intelligence 279
- Computer Vision and Pattern Recognition 157
- Computational Mechanics 147
Countries citing papers authored by C. Eric
This map shows the geographic impact of C. Eric's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by C. Eric with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C. Eric more than expected).
Fields of papers citing papers by C. Eric
This network shows the impact of papers produced by C. Eric. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by C. Eric. The network helps show where C. Eric may publish in the future.
Co-authors
The 25 scholars most cited alongside C. Eric, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 182 | |
| 2 | 2014 | 108 | |
| 3 | 2015 | 70 | |
| 4 | 2016 | 54 | |
| 5 | 2012 | 46 | |
| 6 | 2013 | 38 | |
| 7 | 2015 | 34 | |
| 8 | Convex biclustering: Convex Biclustering | 2017 | 26 |
| 9 | 2021 | 26 | |
| 10 | 2014 | 22 | |
| 11 | 2013 | 21 | |
| 12 | 2012 | 18 | |
| 13 | Provable Convex Co-clustering of Tensors. | 2020 | 12 |
| 14 | 2014 | 11 | |
| 15 | 2019 | 8 | |
| 16 | 2019 | 8 | |
| 17 | 2014 | 6 | |
| 18 | 2018 | 6 | |
| 19 | 2023 | 5 | |
| 20 | 2021 | 5 |
About C. Eric
C. Eric is a scholar working on Computational Mechanics, Artificial Intelligence, Statistics and Probability, Molecular Biology and Computer Vision and Pattern Recognition, having authored 41 papers that have together received 743 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (14 papers), Statistical Methods and Inference (12 papers), Bayesian Methods and Mixture Models (6 papers), Face and Expression Recognition (5 papers), Tensor decomposition and applications (5 papers), Gene expression and cancer classification (5 papers), Advanced Statistical Methods and Models (4 papers) and Advanced Clustering Algorithms Research (4 papers). The work is most often cited by research in Computational Mathematics (170 citations), Statistics and Probability (125 citations), Artificial Intelligence (279 citations), Computer Vision and Pattern Recognition (157 citations) and Computational Mechanics (147 citations). C. Eric has collaborated with scholars based in United States, Poland and France. Frequent co-authors include Kenneth Lange, Tamara G. Kolda, Richard G. Baraniuk, Hua Zhou, Genevera I. Allen, Gary K. Chen, John Michael O. Rañola, David W. Scott, Diego Ortega‐Del Vecchyo and Omid Kohannim. Their work appears in journals such as Journal of Computational and Graphical Statistics, Technometrics, The American Statistician, Scientific Reports and Computational Statistics & Data Analysis.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.